"Tradicional" analysis.

Fourier amplitude of geopotential height

Fourier amplitude of geopotential height

Wave 3 component of the geopotential field of each season at 200hPa.

Wave 3 component of the geopotential field of each season at 200hPa.

Mean wave 3 component of geopotential height between 65°S and 35°S

Mean wave 3 component of geopotential height between 65°S and 35°S

New seasons

First 4 EOFs derived from the 200hPa geopotential zonal anomaly field between 30°S and 80°S with zonal wave 1 filtered out.

First 4 EOFs derived from the 200hPa geopotential zonal anomaly field between 30°S and 80°S with zonal wave 1 filtered out.

Fourier decomposition by latitude of each EOF.

Fourier decomposition by latitude of each EOF.

Monthly mean values for each PC. Colors and shapes divide months into 5 'seasons'.

Monthly mean values for each PC. Colors and shapes divide months into 5 'seasons'.

NO VA. Clústering jerárquico. Cortando en ~0.03 se obtienen 4 clusters, y un 5to separando Abril de ASO por continuidad temporal. Confirma la validez del agrupamiento "a ojo"

NO VA. Clústering jerárquico. Cortando en ~0.03 se obtienen 4 clusters, y un 5to separando Abril de ASO por continuidad temporal. Confirma la validez del agrupamiento "a ojo"

Notes:

  • Making other (still sensible) decisions lead to some differences in clustering. For example, using fields with QS1 and QS2 filtered out puts May closer to April, and December further from JFM. Not surprisingly, a similar result is achieved by using using idealized fields from the reconstructed zonal wave 3 (since higher wavenumbers explain a negligible proportion of the viariance). JFM and ASO (and it's similarity with April), on the other hand, are robust trimesters.

  • This differences imply that the ZW2 might be have an important role in the variability in May and December.

  • JJ is a relatively robust grouping but with obviously more heterogeneous than JFM or ASO

  • Futhermore, removing the linear trend as well as the QS1 field results in a similar classification to the one shown, but the structure of the EOF is slightly different with less separation between wavenumbers (the zonal wave 3 is present in PC1, PC2 and PC3) and a much more asymmetric nature, with higher amplitude anomalies on the western hemisphere than the eastern in the first two PCs and the reverse on the second two. Is it as the wave activity of each hemosphere is separated this way.

Geopotential Fields

Lo anterior justifica el agrupamiento de los meses que viene.

Zonal anomaly of 200hPa geopotential field with zonal wavenumber 1 filtered out. Areas with zonal wind greater than 30 m/s are hatched.

Zonal anomaly of 200hPa geopotential field with zonal wavenumber 1 filtered out. Areas with zonal wind greater than 30 m/s are hatched.

Mean geopotential zonal anomaly with zonal wave 1 filtered out between 65°S and 35°S

Mean geopotential zonal anomaly with zonal wave 1 filtered out between 65°S and 35°S

Zonal anomaly of 200hPa geopotential field with zonal wavenumber 1 and 2 filtered out. Areas with stationary wave number less than 3 are shaded.

Zonal anomaly of 200hPa geopotential field with zonal wavenumber 1 and 2 filtered out. Areas with stationary wave number less than 3 are shaded.

Mean geopotential zonal anomaly with zonal wave 1 and 2 filtered out between 65°S and 35°S

Mean geopotential zonal anomaly with zonal wave 1 and 2 filtered out between 65°S and 35°S

Streamfunction

Mean streamfunction.

Mean streamfunction.

Mean streamfunction with zonal wave 1 filtered out.

Mean streamfunction with zonal wave 1 filtered out.

Mean streamfunction with waves 1 and 2 filtered out.

Mean streamfunction with waves 1 and 2 filtered out.

Fourier

Amplitude of zonal wave 3 for each season defined in the text.

Amplitude of zonal wave 3 for each season defined in the text.

Stationarity, seasonal mean monthly amplitude (MA) and amplitude of the seasonal mean (AM) zonal wave 3 for each season defined in the text.
season stationarity MA AM
DJFM 0.64 35.66 23.50
A 0.62 41.66 26.23
MJJ 0.52 45.22 23.90
ASO 0.54 44.14 24.04
N 0.20 37.18 6.69

Regressions

Regression between PCs and gh.

Regression between PCs and gh.

Regression between PCs and Psi.

Regression between PCs and Psi.

Regression of standarized PC with antarctic sea ice concentrations.

Regression of standarized PC with antarctic sea ice concentrations.

Regression of standarized PC with SST.

Regression of standarized PC with SST.

Correlation between ONI and each principal component
PC estimate p.value
PC1 -0.25 0.000000668
PC2 0.13 0.013721337

Regression between OLR and PCs

Regression between OLR and PCs

Regression between precipitation and PCs

Regression between precipitation and PCs

Regression between 100hPa temperature and PCs

Regression between 100hPa temperature and PCs

Cosas para hacer

  • Usar datos de ERA
  • Período más largo (1980-20017?)
  • ¿Eliminar tendencia lineal? (Hobbs y Raphael)
  • ¿Cómo poner wavelets?

Epílogo:

¿Qué pasa si hago EOF filtrando también la tendencia lineal?

First 4 EOFs derived from the 200hPa geopotential zonal anomaly field between 30°S and 80°S with zonal wave 1 and linear trend filtered out

First 4 EOFs derived from the 200hPa geopotential zonal anomaly field between 30°S and 80°S with zonal wave 1 and linear trend filtered out

Linear combination of PC1 and PC3 (PCodd) and of PC2 and PC4 (PCeven)

Linear combination of PC1 and PC3 (PCodd) and of PC2 and PC4 (PCeven)

Fourier decomposition by latitude of each EOF.

Fourier decomposition by latitude of each EOF.

Monthly mean values for each PC. Colors and shapes divide months into 5 'seasons'.

Monthly mean values for each PC. Colors and shapes divide months into 5 'seasons'.

NO VA. Clústering jerárquico"

NO VA. Clústering jerárquico"

Linear regrssions of geopotential height (full) and geopotential height with zonal wave1 removed (no.1)

Linear regrssions of geopotential height (full) and geopotential height with zonal wave1 removed (no.1)